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Wu et al., 2023 - Google Patents

KPRLN: deep knowledge preference-aware reinforcement learning network for recommendation

Wu et al., 2023

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Document ID
14558563320436958979
Author
Wu D
Tang M
Zhang S
You A
Gao W
Publication year
Publication venue
Complex & Intelligent Systems

External Links

Snippet

User preference information plays an important role in knowledge graph-based recommender systems, which is reflected in users having different preferences for each entity–relation pair in the knowledge graph. Existing approaches have not modeled this fine …
Continue reading at link.springer.com (HTML) (other versions)

Classifications

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    • G06F17/30861—Retrieval from the Internet, e.g. browsers
    • G06F17/30864—Retrieval from the Internet, e.g. browsers by querying, e.g. search engines or meta-search engines, crawling techniques, push systems
    • G06F17/30867—Retrieval from the Internet, e.g. browsers by querying, e.g. search engines or meta-search engines, crawling techniques, push systems with filtering and personalisation
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    • G—PHYSICS
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